Developing an adaptive algorithm for information hiding in video streams

Abstract

Steganography is the art and science of secret communication. Modern cover types can take different forms. Nowadays, video streams are transmitted more frequently on internet websites imposing a larger practical significance on video steganography. A video can be considered a sequence of images. Information hiding in video has a variety of techniques. Although great efforts were done in developing these techniques, but most of them suffer from intolerance to video processing attacks and lack any intelligent processing of the cover video. Adaptive video steganography was recently proposed in the literature. It aims to achieve better quality of the stego-video by intelligently processing the cover according to some criteria. This helps to identify the best regions for data hiding, referred to as Regions Of Interest (ROI). A recent research by Cheddad et al. showed that data embedding in human skin regions as ROI yield better imperceptibility and increase the hiding robustness. In this work, a blind adaptive algorithm for robust video steganography is proposed. The proposed algorithm adaptively processes the cover video and hides data in its human skin regions. A skin map is created for each frame using a fast adaptive skin detection method. Then a blocking step is applied on the produced skin-map converting it into a skin-block-map for discarding the error-prone skin pixels and enhancing the extraction quality. Next, the skin-block-map is used for guiding the embedding procedure. Finally, the secret bits are embedded in the detail coefficients of the red and blue components of each frame using a wavelet quantization-based algorithm for achieving robustness against MPEG-4 compression. Hiding capacity, imperceptibility, extraction accuracy and robustness against MPEG-4 compression of the proposed algorithm were tested. Results show the high imperceptibility of the proposed algorithm and its robustness against MPEG-4 compression.